Online shopping is a form of electronic commerce where goods and/or services can be bought, purchased, and/or traded using the Internet. For example, the goods and/or services may be located online by entering a search query into a web search engine, and allowing the search engine to search the Internet for the goods and/or services identified in the search query.
Web search engines typically rely on text matching for locating relevant goods and/or services on the Internet. For example, the search engine may return particular items that are an exact match with the search query. However, in some instances, multiple users may formulate similar search queries when looking for different goods and/or services. For example, a first user may formulate the search query “apples” when searching for the grocery item apples, while a second user may formulate the search query “apple” when searching for electronic devices manufactured by Apple, Inc. In instances where the user enters the search query “apple” intending to find the grocery item “apples”, the user may have a poor search experience if the search engine returns electronic devices rather than grocery items.
Query normalization is an out-of-the-box ontology technique for formulating stemming pairs for a search query. However, this ontology technique may not be able to recognize specific brand names, specific product names, and/or retail-specific jargon. In addition, query normalization, which relies on text-matching, may generate results corresponding to that particular search query only. However, the user may have entered the search query with an intent to locate items other than what the search engine located, utilizing text-matching, for that particular the search query. For instance, the user may have entered the query “chair” with the intent of locating dining room chairs and the search engine (utilizing query normalization) may have located office chairs instead. This may lead to a poor search experience by the user. Therefore, query normalization based on text-matching alone, and as currently used, may not be able to generate most, if not all suitable items based on a particular search query.
The present disclosure is aimed at solving the problems identified above.